Extended Reality System for Robotic Learning from Human Demonstration
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913508373823488 |
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| author | Ngui, Isaac McBeth, Courtney He, Grace Santos, André Corrêa Soares, Luciano Morales, Marco Amato, Nancy M. |
| author_facet | Ngui, Isaac McBeth, Courtney He, Grace Santos, André Corrêa Soares, Luciano Morales, Marco Amato, Nancy M. |
| contents | Many real-world tasks are intuitive for a human to perform, but difficult to encode algorithmically when utilizing a robot to perform the tasks. In these scenarios, robotic systems can benefit from expert demonstrations to learn how to perform each task. In many settings, it may be difficult or unsafe to use a physical robot to provide these demonstrations, for example, considering cooking tasks such as slicing with a knife. Extended reality provides a natural setting for demonstrating robotic trajectories while bypassing safety concerns and providing a broader range of interaction modalities. We propose the Robot Action Demonstration in Extended Reality (RADER) system, a generic extended reality interface for learning from demonstration. We additionally present its application to an existing state-of-the-art learning from demonstration approach and show comparable results between demonstrations given on a physical robot and those given using our extended reality system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_12862 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Extended Reality System for Robotic Learning from Human Demonstration Ngui, Isaac McBeth, Courtney He, Grace Santos, André Corrêa Soares, Luciano Morales, Marco Amato, Nancy M. Robotics Human-Computer Interaction Many real-world tasks are intuitive for a human to perform, but difficult to encode algorithmically when utilizing a robot to perform the tasks. In these scenarios, robotic systems can benefit from expert demonstrations to learn how to perform each task. In many settings, it may be difficult or unsafe to use a physical robot to provide these demonstrations, for example, considering cooking tasks such as slicing with a knife. Extended reality provides a natural setting for demonstrating robotic trajectories while bypassing safety concerns and providing a broader range of interaction modalities. We propose the Robot Action Demonstration in Extended Reality (RADER) system, a generic extended reality interface for learning from demonstration. We additionally present its application to an existing state-of-the-art learning from demonstration approach and show comparable results between demonstrations given on a physical robot and those given using our extended reality system. |
| title | Extended Reality System for Robotic Learning from Human Demonstration |
| topic | Robotics Human-Computer Interaction |
| url | https://arxiv.org/abs/2409.12862 |